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Exploring Populations: How can I best understand and represent a population?

We don’t often speak to everyone we wish to speak about - so understanding populations often involves: sampling investigating concluding and attempting to argue the broader

applicability of our findings

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The Sampling Process The process of sample selection

involves: naming your population determining sample size and employing appropriate sampling

strategies

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Naming your Population Populations are commonly made up of

individuals, but can be made up of households, workplaces, or events

Populations are then narrowed through defining characteristics such as geographic range. Additional defining characteristics include age, class, gender, and/ or race – or in the case of an organization, number of employees, years of operation, type of business, etc.

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Determining Sample Size Sample size very much depends on the

nature of your research and the shape and form of the data you intend to collect

The best way to come up with a figure is to consider: your goals (transferability or generalizability) the parameters of your population (size and

how easy it is to identify and find its elements)

and the type of data you plan to collect

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Random Sampling Random sampling refers to sampling

strategies that give every element of a population an equal chance of selection. Strategies include: simple random sampling systematic sampling stratified random sampling and cluster sampling

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Simple Random Sampling

In simple random sampling all elements of a population have an equal chance of inclusion. It is considered ‘fair’, but rarely used in practice because the process demands: identification of all elements of the population; lists of all those elements; and finally a way of randomly selecting from this list.

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Systematic Sampling

Systematic sampling involves selecting every nth case within a defined population. It may involve going to every 10th house or selecting every 20th person on a list. It is easier to do than devising methods for random selection, and offers a close approximation of random sampling as long as the elements are randomly ordered.

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Stratified Random Sampling

Stratified random sampling involves dividing your population into various subgroups and then taking a simple random (or systematic) sample within each one.

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Cluster Sampling

Cluster sampling involves surveying whole clusters of the population selected through a defined random sampling strategy. The thinking here is that the best way to find high school students is through high schools; or the best way to find church goers is through churches.

 

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Non-Random Sampling Non-random sampling refers to strategic requests for ‘volunteers’; the use of informants that ‘snowball’; or ‘hand picking’ respondents

Keep in mind that selecting a sample on the basis of convenience alone can threaten a study's credibility

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Handpicked Sampling

             

                                             

Handpicked sampling involves selecting cases that meet particular criteria; are considered typical; show wide variance; represent ‘expertise’; or cover a range of possibilities.

Other options include the selection of critical, extreme, deviant, or politically important cases.

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Snowball Sampling

   

         

 

   

   

   

     

Snowball sampling is often used for populations that are not easily identified or accessed; and involves building a sample through referrals, i.e.) you identify someone from your population willing to be in your study. You then ask them to identify others who meet the study criteria. Each of those individuals is then asked for further recommendations.

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Volunteer Sampling

           

           

     

     

Volunteer sampling simply refers to the process of selecting a sample by asking for volunteers. This may involve putting an ad in the newspaper or going to local organizations such as churches, schools, or community groups.

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Qualitative Field Research Attitudes and behaviors best

understood in a natural setting. Social processes over time.

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Elements of Social Life Appropriate to Field Research

Practices: talking, reading a book Episodes: divorce, crime, illness Encounters: people meeting and

interacting Role: occupations, family roles Relationships: friendships, family

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Elements of Social Life Appropriate to Field Research

Groups: cliques, teams, work groups Organizations: hospitals, schools Settlements: neighborhoods,

ghettoes Social worlds: "wall street", "the

sports world“ Lifestyles (subcultures): urban,

homeless

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Field Research Paradigms Naturalism Ethnomethodology Case studies and the extended

case method Institutional ethnography Participatory action research

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Preparing for Field Work Fill in your knowledge of the

subject. Discuss the group you plan to

research with an informant. Develop an identity with the people

to be studied. Realize that your initial contact with

the group can influence your observations.

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Seven Stages of Interviewing

1. Thematizing 2. Design3. Interviewing4. Transcribing

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Seven Stages of Interviewing

5. Analyzing6. Verifying and checking facts7. Reporting

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Focus Groups Socially oriented research method Flexible High face validity Speedy results Low in cost

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Disadvantages of Focus Groups Less control than individual

interviews. Data can be difficult to analyze. Moderators must be skilled. Difference between groups can be

troublesome. Groups are difficult to assemble. Discussion must be conducted in a

conducive environment.

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Guidelines - Taking Research Notes Don’t trust your memory. Take notes

while you observe. Take sketchy notes in the field and

rewrite them later, filling in the details (ASAP!!!).

Record everything.• Things that don't seem important may turn

out to be significant. Realize that most of your field notes will

not be reflected in your final project.

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Strengths of Field Research Permits a great depth of

understanding. Flexibility - research may be

modified at any time. Inexpensive Has more validity than surveys or

experiments.

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Weaknesses of Field Research Qualitative and not appropriate for

statistical descriptions of populations.

Has potential problems with reliability since field research methods are often personal.

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Unobtrusive Research

1. Content analysis - examine written documents such as editorials.

2. Analyses of existing statistics.3. Historical/comparative analysis -

historical records.

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Strengths of Content Analysis Economy of time and money. Easy to repeat a portion of the

study if necessary. Permits study of processes over

time. Researcher seldom has any effect

on the subject being studied. Reliability.

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Weaknesses of Content Analysis Limited to the examination of

recorded communications. Problems of validity are likely.

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Analyzing Existing Statistics Can be the main source of data or

a supplemental source of data. Often existing data doesn't cover

the exact question. Reliability is dependent on the

quality of the statistics.

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Comparative and Historical Analysis

Cautions: Can't trust the accuracy of records

- official or unofficial, primary or secondary.

Must be wary of bias in data sources.